Methods and systems to browse data items

ABSTRACT

Methods and Systems to browse data items. There is provided a method and system to enable a buyer to browse listings that are listed by sellers on a network-based marketplace and stored in a data resource. There is further provided a method to cancel characteristics used to identify listings that are listed by sellers on a network-based marketplace.

RELATED APPLICATIONS

The present application claims the priority benefit of U.S. ProvisionalApplication Ser. No. 60/666,549, filed Mar. 30, 2005, which isincorporated herein by reference.

TECHNICAL FIELD

This application relates generally to the technical field of datacommunication and, in one example embodiment, methods and system tobrowse data items.

BACKGROUND

A user searching for information in a network based marketplace issometimes hindered by a user interface that does not permit the additionof multiple search constraints or a user interface that does not permitthe user to remove specific search constraints. Buyers are limited fromadding multiple search constraints for execution in a single search withregard to a single concept. For example, a buyer searching for Reebokand Adidas tennis shoes with a single search is prohibited fromselecting more than one of the previously mentioned brands (e.g.,concept) from a user interface. In addition, users are further limitedto removing only the most recently entered search constraint even thoughmultiple constraints may have been entered.

SUMMARY OF INVENTION

There is provided a method to enable a buyer to browse listings that arelisted by sellers on a network-based marketplace and stored in a dataresource. The method includes generating a user interface, the userinterface displaying a concept and at least two values that areassociated with the concept; and receiving at least two selections froma buyer that correspond to the at least two values, the two selectionsutilized to identify at least one listing that is stored in the dataresource and is associated with the at least two values based on anevaluation of information that is entered by the seller.

There is further provided a method to cancel characteristics used toidentify listings that are listed by sellers on a network-basedmarketplace. The method includes communicating a plurality ofcharacteristics, utilized to identify listings, to a user; receiving aselection from the user that cancels a characteristic other than a mostrecently selected characteristic; based on the selection, identifying aplurality of remaining characteristics that includes the most recentlyselected characteristic to identify at least one listing that isdetermined to exhibit the remaining characteristics based on anevaluation of information that is entered by a seller; and communicatingthe plurality of remaining characteristics and the at least one listingto the user.

BRIEF DESCRIPTION OF THE DRAWINGS

Embodiments of the present invention are illustrated by way of exampleand not limitation in the figures of the accompanying drawings, in whichlike references indicate similar elements and in which:

FIG. 1 is a block diagram illustrating a system, according to anembodiment, to search a data resource;

FIG. 2 is a network diagram depicting a system, according to oneembodiment, to search a data resource;

FIG. 3 is a block diagram illustrating multiple applications that, inone example embodiment of the present invention, are provided as part ofthe computer-based system;

FIG. 4 is a high-level entity-relationship diagram, illustrating varioustables that are utilized by and support the network-based applications,according to an example embodiment of the present invention;

FIG. 5 is a block diagram illustrating a system, according to anembodiment, facilitate a search of a data resource;

FIG. 6 is a block diagram illustrating search applications and searchrelated data structures, according to an embodiment, to classify aninformation item;

FIG. 7 is a block diagram illustrating search metadata, according to anembodiment;

FIG. 8 is a block diagram illustrating a method, according to anembodiment, to facilitate searching a data resource;

FIG. 9 is a block diagram illustrating a method, according to anembodiment, to evaluate information with a classification rule;

FIG. 10 is a block diagram illustrating a method, according to anembodiment, to evaluate information with an inference rule;

FIG. 11 is a block diagram illustrating a system, according to anembodiment, to generate a query;

FIG. 12 is a block diagram illustrating search applications and searchmetadata, according to an embodiment;

FIG. 13 is a block diagram illustrating a method, according to anembodiment, to generate a query to search a data resource;

FIG. 14 is a block diagram illustrating a method, according to anembodiment, to determine domains based on a keyword query;

FIG. 15 is a block diagram illustrating a method, according to anembodiment, to determine selected characteristics based on a keywordquery and a domain;

FIG. 16 is a block diagram illustrating a system, according to anembodiment, to identify data items for browsing;

FIG. 17 is a block diagram illustrating search applications and searchmetadata, according to an embodiment;

FIG. 18 is a block diagram illustrating a classification engine,according to an embodiment;

FIG. 19 is a block diagram illustrating a method, according to anembodiment, to identify data items for browsing;

FIG. 20 is a block diagram illustrating a method to generate a userinterface based on selected characteristics, according to an embodiment;

FIG. 21 is a block diagram illustrating a method, according to anexample embodiment, to determine a set of items based on selectedcharacteristics;

FIG. 22 is a block diagram illustrating a method, according to anembodiment, to determine browsing sets;

FIG. 23 is a block diagram illustrating a method, according to anembodiment, to generate counts for browsing values;

FIG. 24 is a block diagram illustrating user interfaces and browsercontrols, according to an embodiment;

FIG. 25 is a block diagram illustrating a system, according to anembodiment, to process a browser back button;

FIG. 26 is a block diagram further illustrating software componentsassociated with the client machine, according to an embodiment;

FIG. 27 is an interactive flow chart illustrating a method, according toan embodiment, to process a back button at a client machine;

FIG. 28 is an interactive flow chart illustrating a method, according toan embodiment, to request a user interface;

FIG. 29A illustrate a method, according to an embodiment, to process auser selection of the “more” user interface element;

FIG. 29B illustrate a method, according to an embodiment, to process auser selection of the “ALL” user interface element;

FIG. 29C illustrate a method, according to an embodiment, to process auser selection of the back button;

FIGS. 30-40 illustrate user interface screens, according to an exampleembodiment of the present invention; and

FIG. 41 illustrates a diagrammatic representation of a machine in theexample form of a computer system within which a set of instructions,for causing the machine to perform any one or more of the methodologiesdiscussed herein, may be executed.

DETAILED DESCRIPTION

Methods and systems to facilitate browse data items are described. Inthe following description, for purposes of explanation, numerousspecific details are set forth in order to provide a thoroughunderstanding of the present invention. It will be evident, however, toone skilled in the art that the present invention may be practicedwithout these specific details.

According to a first aspect there is provided a method and system tofacilitate searching of a data resource. The system receives informationfrom a seller, that is associated with an item and evaluates thereceived information in real time with a rule that includes anexpression (e.g., Boolean) and supplemental information. If theexpression evaluates true, the system associates and stores, in realtime, the supplemental information with the received information in adata resource. The supplemental information may include classificationinformation and inferential information. The classification informationmay be utilized to structure the information according to concepts thatmay be later utilized to search the information. The inferentialinformation be inferred from the received information (e.g., the colorred may be inferred from the color ruby because ruby is a type of red)and may also be later utilized to search the information.

According to a second aspect there is provided a method and system togenerate a query to search a data resource utilized by a seller and abuyer that transact an item in a network-based marketplace. The systemreceives a keyword query, from a buyer, and evaluates the keywords inthe keyword query with a rule that includes an expression (e.g.,Boolean) and classification information. If the expression evaluatestrue, then the system generates a concept query that corresponds to thekeyword query and includes the classification information. The conceptquery may subsequently be used to search information in a data resource(e.g., query) that includes the classification information (e.g.,according to the first aspect described above) that is generated frominformation that is entered by the seller.

According to a third aspect there is provided a method and system toenable a buyer to browse listings that are listed by sellers on anetwork-based marketplace. The system generates a user interface thatdisplays a concept and multiple values that are associated with theconcept. The system may receive two or more selections from the buyerthat correspond to values that may be utilized to identify the listingson the network-based marketplace. For example, a user interface forshoes may include brands (e.g., concept) and brand names including Nike,Reebok, Keds, etc. (e.g., values). The buyer may then select two or morebrand names that are received by the system and utilized by the systemto identify and display shoes that exhibit the selected values (e.g.,Nike and Reebok) based on information entered by the seller.

According to a fourth aspect there is provided a method and system tocancel characteristics used to identify data listings that are listed bysellers on a network-based marketplace. The system communicates a set ofcharacteristics, utilized to identify listings that may have beenselected by a user to identify data items. The user may then cancel acharacteristic other than a most recently selected characteristic. Inresponse, the system may utilize the remaining characteristics toidentify data items that are determined to exhibit the remainingcharacteristics based on an evaluation of information that is entered bythe seller.

According to a fifth aspect there is provided a method and system todetermine the size of an area associated with a user interface that isutilized to display data items to a user. The system receives a requestfor a user interface that includes two areas that are complementary insize. The system uses the first area to display data items and thesecond area to display browsing options that may be selected by the userto identify data items in a data source. The system automaticallydetermines a size associated with the area to display data items bycomputing a number of data items that are to be displayed in the firstarea. If the number of data items to be displayed in the first areaexceeds a predetermined threshold then the system decreases the area todisplay data items and increases the area associated with the browsingoptions. Accordingly, a high count of data items may trigger thegeneration of user interface that emphasizes browsing options that maybe selected by the user to identify data items in a data source.

According to a sixth aspect there is provided a method and system toprocess a selection of a browser back button at a client computer. Thesystem, at the client computer, receives a browser back button selectionthat is processed by a browser that retrieves a user interface that doesnot include displayable user interface elements. The identity of theretrieved user interface is monitored by a client application program(e.g., script, applet, etc.) that utilizes the identity of the requesteduser interface to identify a user interface that the user expects to bedisplayed responsive to selection of the back button.

Overview

FIG. 1 is a block diagram illustrating a computer-based system 11,according to an embodiment, to search a data resource. The system 11 isdescribed to provide an example context for what follows. At operation13, an author or publisher (e.g., a seller) enters information includinginformation items (e.g., an item description) into a client computer.The client computer communicates the information to the system 11 (e.g.,a computer-based system), where it is stored in a database. The itemdescription (or listing) may include a title, a description, one or morelisting categories, etc.

At operation 15, a classification engine determines a domain for thereceived information (e.g., whether the item description relates to ashoe, toy, book, etc.), adds classification and inference tags to thereceived information and stores the classification tags and theinference tags with the received information in a data resource (e.g.,memory, database, storage device, etc.). The classification enginedetermines a domain for the item by applying domain specific queries tothe item. The classification engine may add classification tags to thereceived information responsive to the application of classificationrules to the received information. For example, the classificationengine may read “ruby” (e.g., item information) and respond bygenerating “color=ruby” (e.g., classification tag). Accordingly, theitem information “ruby” is structured under the concept “color.” Inaddition, the classification engine may add inference tags responsive tothe application of inference rules to the item information and theclassification tags. For example, the classification engine may read“color=ruby” (e.g., classification tag) and respond by generating“color=red” (e.g., inference tag). Accordingly, the inference tag“color=red” adds information to the item information by inferring that“ruby” is a type of “red.”

At operation 17, a user enters a keyword query that is received by aclient computer that communicates the keyword query to thecomputer-based system 11.

At operation 19, the keyword query is received and utilized by searchapplications to generate a domain and a conceptual query. For examplethe keyword query “Nike Black Size 8” may be utilized to generate thedomain “shoes” and the conceptual query “Brand=Nike”, “Color=black”,Size=Size 8.”

At operation 21, the domain and the conceptual query are received by theclassification engine and utilized to find information (e.g., itemlistings) for presentation to the buyer. Continuing with the presentexample, the classification engine may search for item listings in thedomain “shoes” that includes classification tags or inference tags thatmatch the conceptual query “Brand=Nike” or “Color=black” or Size=Size8.”

At operation 23, the search applications may determine browsing sets toenable the user to further refine their search. A browsing set mayinclude a browsing concept (e.g., Price Range) and multiple browsingvalues (e.g., $1.00 to $5.00, $5.00 to $10.00, $10.00 to $15.00). Theuser may select a browsing value which effectively specifies a browsingcharacteristic, a browsing concept—browsing value pair (e.g., PriceRange—$1.00-$5.00). Accordingly, the search applications may determinemultiple browsing characteristics that may be selected by the user.

At operation 25, the computer-based system 11 presents the conceptquery, the domain, the multiple browsing characteristics, and the listof items to the user.

DEFINITIONS

The word “value” in this document means numerical information or textualinformation or numerical information signifying textual information(e.g., 1=Red, 2=Blue, etc.) or textual information signifying numericalinformation or any combination thereof.

The phrase “real time” in this document means with little or no delay.

Platform Architecture

FIG. 2 is a network diagram depicting a system 10, according to oneembodiment, having a client-server architecture. A computer-based systemplatform 12 (e.g., a computer-based system) provides server-sidefunctionality, via a network 14 (e.g., the Internet) to one or moreclients. FIG. 2 illustrates, for example, a web client 16 (e.g., abrowser, such as the Internet Explorer browser developed by MicrosoftCorporation of Redmond, Wash. State), and a programmatic client 18executing on respective client machines 20 and 22.

Turning specifically to the computer-based system 12, an ApplicationProgram Interface (API) server 24 and a web server 26 are coupled to,and provide programmatic and web interfaces respectively to, one or moreapplication servers 28. The application servers 28 host one or moreapplications 30. The application servers 28 are, in turn, shown to becoupled to one or more databases servers 34 that facilitate access toone or more databases 36. The computer-based system 12 is further shownto include an administrator 33 may enter metadata (e.g., searchmetadata) that may be stored via the database servers 34 in the database36.

The applications 30 provide a number of commerce functions and servicesto users that access the computer-based system 12.

Further, while the system 10 shown in FIG. 2 employs a client-serverarchitecture, the aspects described in this application of course arenot limited to such an architecture, and could equally well findapplication in a distributed, or peer-to-peer, architecture system. Thevarious applications 30 and 32 could also be implemented as standalonesoftware programs, which do not necessarily have networkingcapabilities.

The web client 16, it will be appreciated, accesses the variousapplications 30 via the web interface supported by the web server 26.Similarly, the programmatic client 18 accesses the various services andfunctions provided by the applications 30 via the programmatic interfaceprovided by the API server 24. The programmatic client 18 may, forexample, be a seller application (e.g., the TurboLister applicationdeveloped by eBay Inc., of San Jose, Calif.) to enable sellers to authorand manage listings on the computer-based system 12 in an off-linemanner, and to perform batch-mode communications between theprogrammatic client 18 and the computer-based system 12.

FIG. 2 also illustrates a third party application 38, executing on athird party server machine 40, as having programmatic access to thecomputer-based system 12 via the programmatic interface provided by theAPI server 24. For example, the third party application 38 may,utilizing information retrieved from the computer-based system 12,support one or more features or functions on a website hosted by thethird party. The third party website may, for example, provide one ormore promotional, commerce or payment functions that are supported bythe relevant applications of the computer-based system 12.

Applications

FIG. 3 is a block diagram illustrating multiple applications 30 that, inone example embodiment, are provided as part of the computer-basedsystem 12. In an exemplary embodiment in which the computer-based systemmay support a network-based marketplace, the computer-based system 12may provide a number of listing and price-setting mechanisms whereby aseller may list goods or services for sale, a buyer can express interestin or indicate a desire to purchase such goods or services, and a pricecan be set for a transaction pertaining to the goods or services. Tothis end, the applications 30 are shown to include one or more auctionapplications 44 which support auction-format listing and price settingmechanisms (e.g., English, Dutch, Vickrey, Chinese, Double, Reverseauctions etc.). The various auction applications 44 may also provide anumber of features in support of such auction-format listings, such as areserve price feature whereby a seller may specify a reserve price inconnection with a listing and a proxy-bidding feature whereby a biddermay invoke automated proxy bidding.

A number of fixed-price applications 46 support fixed-price listingformats (e.g., the traditional classified advertisement-type listing ora catalogue listing) and buyout-type listings. Specifically, buyout-typelistings (e.g., including the Buy-It-Now (BIN) technology developed byeBay Inc., of San Jose, Calif.) may be offered in conjunction with anauction-format listing, and allow a buyer to purchase goods or services,which are also being offered for sale via an auction, for a fixed-pricethat is typically higher than the starting price of the auction.

Store applications 48 allow sellers to group their listings within a“virtual” store, which may be branded and otherwise personalized by andfor the sellers. Such a virtual store may also offer promotions,incentives and features that are specific and personalized to a relevantseller.

Reputation applications 50 allow parties that transact utilizing thecomputer-based system 12 to establish, build and maintain reputations,which may be made available and published to potential trading partners.Consider that where, for example, the computer-based system 12 supportsperson-to-person trading, users may have no history or other referenceinformation whereby the trustworthiness and credibility of potentialtrading partners may be assessed. The reputation applications 50 allow auser, for example through feedback provided by other transactionpartners, to establish a reputation within the computer-based system 12over time. Other potential trading partners may then reference such areputation for the purposes of assessing credibility andtrustworthiness.

Personalization applications 52 allow users of the computer-based system12 to personalize various aspects of their interactions with thecomputer-based system 12. For example a user may, utilizing anappropriate personalization application 52, create a personalizedreference page at which information regarding transactions to which theuser is (or has been) a party may be viewed. Further, a personalizationapplication 52 may enable a user to personalize listings and otheraspects of their interactions with the computer-based system 12 andother parties.

In one embodiment, the computer-based system 12 may support a number ofcommerce systems that are customized, for example, for specificgeographic regions. A version of the computer-based system 12 may becustomized for the United Kingdom, whereas another version of thecomputer-based system 12 may be customized for the United States. Eachof these versions may operate as an independent commerce system, or maybe customized (or internationalized) presentations of a commonunderlying commerce system.

Navigation and such of a service (e.g., the network-based marketplace)supported by the computer-based system 12 may be facilitated by one ormore search applications 57. For example, the search applications 57 mayenable the classification of information (e.g., item listings) publishedvia the computer-based system 12, and may also enable the subsequentsearching of the items with keyword queries, concept queries, andmulti-path browsing.

In order to make information, available via the computer-based system12, as visually informing and attractive as possible, the applications30 may include one or more imaging applications 58 utilizing which usersmay upload images for inclusion within listings. An imaging application58 also operates to incorporate images within viewed information. Theimaging applications 58 may also support one or more promotionalfeatures, such as image galleries that are presented to potentialbuyers. For example, sellers may pay an additional fee to have an imageincluded within a gallery of images for promoted item information.

Authoring/publishing applications, in the example form of the listingcreation applications 60, allow authors/publishers sellers convenientlyto author information (e.g., listings pertaining to goods or servicesthat they wish to transact via the computer-based system 12), andapplication management applications (e.g., listing managementapplications 62) allow authors/publishers to manage such publishedinformation. For example, where a particular seller has authored and/orpublished a large number of listings, the management of such listingsmay present a challenge. The listing management applications 62 providea number of features (e.g., auto-relisting, inventory level monitors,etc.) to assist the seller in managing such listings. One or morepost-listing management applications 64 also assist sellers with anumber of activities that typically occur post-listing. For example,upon completion of an auction facilitated by one or more auctionapplications 44, a buyer may wish to leave feedback regarding aparticular seller. To this end, a post-listing management application 64may provide an interface to one or more reputation applications 50, soas to allow the buyer conveniently to provide feedback regarding aseller to the reputation applications 50. Feedback may take the form ofa review that is registered as a positive comment, a neutral comment ora negative comment. Further, points may be associated with each form ofcomment (e.g., +1 point for each positive comment, 0 for each neutralcomment, and −1 for each negative comment) and summed to generate arating for the seller.

Dispute resolution applications 66 provide mechanisms whereby disputesarising between transacting parties may be resolved. For example, thedispute resolution applications 66 may provide guided procedures wherebythe parties are guided through a number of steps in an attempt to settlea dispute. In the event that the dispute cannot be settled via theguided procedures, the dispute may be escalated to a third partymediator or arbitrator.

A number of outlying behavior applications 68 implement various frauddetection and prevention mechanisms to reduce the occurrence of fraudwithin the computer-based system 12, and customer segmentationmechanisms to identify and classify high value users.

Messaging applications 70 are responsible for the generation anddelivery of messages to users of the computer-based system 12, suchmessages for example advising users regarding the status of listings atthe computer-based system 12 (e.g., providing “outbid” notices tobidders during an auction process or to provide promotional andmerchandising information to users).

Merchandising applications 72 support various merchandising functionsthat are made available to sellers to enable sellers to increase salesvia the computer-based system 12. The merchandising applications 72 alsooperate the various merchandising features that may be invoked bysellers, and may monitor and track the success of merchandisingstrategies employed by sellers.

The computer-based system 12 itself, or one or more parties thattransact via the computer-based system 12, may operate loyalty programsthat are supported by one or more loyalty/promotions applications 74.For example, a buyer may earn loyalty or promotions points for eachtransaction established and/or concluded with a particular seller, andbe offered a reward for which accumulated loyalty points can beredeemed.

Data Structures

FIG. 4 is a high-level entity-relationship diagram, illustrating varioustables 90 that may be maintained within the databases 36, and that areutilized by and support the applications 30. While the exampleembodiment of the present invention is described as being at leastpartially implemented utilizing a relational database, other embodimentsmay utilize other database-architectures (e.g., an object-orienteddatabase schema) or data organization structures.

A user table 92 contains a record for each registered user of thecomputer-based system 12, and may include identifier, address andfinancial instrument information pertaining to each such registereduser. In one embodiment, a user may operate as an author/publisher(e.g., seller) and information consumer (e.g., a buyer), or both, withinthe computer-based system 12. In one example embodiment of the presentinvention, a buyer may be a user that has accumulated value (e.g.,commercial or proprietary currency), and is then able to exchange theaccumulated value for items that are offered for sale by thecomputer-based system 12.

The tables 90 also include an items table 94 in which are maintaineditem records for goods and services (e.g., items) that are available tobe, or have been, transacted via the computer-based system 12. Each itemrecord within the items table 94 may furthermore be linked to one ormore user records within the user table 92, so as to associate a sellerand one or more actual or potential buyers with each item record.

A search metadata table 152 includes search metadata to classify iteminformation and search information (e.g., classification rules andinference rules) and to display browsing characteristics (e.g., displayinstructions).

A transaction table 96 contains a record for each transaction (e.g., apurchase transaction) pertaining to items for which records exist withinthe items table 94.

An order table 98 is populated with order records, each order recordbeing associated with an order. Each order, in turn, may be with respectto one or more transactions for which records exist within thetransactions table 96.

Bid records within a bids table 100 each relate to a bid received at thecomputer-based system 12 in connection with an auction-format listingsupported by an auction application 44. A feedback table 102 is utilizedby one or more reputation applications 50, in one example embodiment, toconstruct and maintain reputation information concerning users. Ahistory table 104 maintains a history of transactions to which a userhas been a party. One or more attributes tables including an itemattributes table 105 that records attribute information pertaining toitems for which records exist within the items table 94 and a userattributes table 106 that records attribute information pertaining tousers for which records exist within the user table 92.

Searching a Data Resource

FIG. 5 is a block diagram illustrating a system 81, according to anembodiment, to facilitate a search of a data resource. The system 81 isdescribed to provide an example overview for what follows. The system 81includes a classification engine 83, classification rules 89, andinference rules 91. The classification engine 83 is shown to receive aninformation (e.g., an item listing 85) from an author/publisher (e.g., aseller 87), generate a tagged item information 93 (e.g., a tagged itemlisting 93) that includes classification tags 97, inference tags 99 andstore the tagged item information 93 in the classification engine 83.The classification engine 83 utilizes the classification rules 89 andthe inference rules 91 to generate and apply the classification tags 97and the inference tags 99 to the information.

FIG. 6 is a block diagram illustrating search applications 57 and searchrelated data structures, according to an embodiment, to classifyinformation (e.g., item information). The search applications 57 includea receiving module 422 and a classification engine 83. The receivingmodule 422 may receive information or information items (e.g., iteminformation 120) that may have been entered by a user (e.g., a seller)from a client machine. The receiving module 422 may add cataloginformation to the item information 120, store the item information 120in a database and communicates the item information 120 to theclassification engine 83. The classification engine 83 includes aprocessing module 116, a rule application module 118 and taggedinformation (e.g., tagged item information 93). The tagged iteminformation 93 includes item information 120 and item classificationinformation 131.

The processing module 116 associates one or more domains 130 with theitem information 120 and generates a set of item classificationinformation 131 for each domain 130. Finally, the processing module 116stores the item information 120, item classification information 131,and domains 130 in the classification engine 83.

The rule application module 118 applies classification rules andinference rules to generate classification tags 97 and/or inference tags99 tags that are stored in the item classification information 131.

The item information 120 includes a title 122, a description 124, one ormore listing categories 126, one or more optional item specifics 128,price information 101, selling format 103, payment method 121, shippinginformation 123, item location 125, buyer requirements 127, andmiscellaneous information 145. The title 122 may include information inthe form of alphanumeric strings that are entered by the user to providea title for the item information 120. The description 124 may includeinformation in the form of alphanumeric strings, pictures (e.g., JPEG,MPEG, etc.), illustrations, etc. The listing category 126 may includeone or more listing categories selected by the user within which to listthe item information 120 on the computer-based system 12. The itemspecific 128 is shown to include an attribute 132 and a value 134. Thevalue 134 may be entered by a user from a pull down menu. For instance,item information 120 relating to a “shoe” may be associated with an itemspecific 128 “brand” that includes a pull down menu that lists differentvalues 134 that correspond to brands of shoe manufacturers (e.g.,Reebok, Nike, etc.). The price information 101 may include a startingprice for an auction, an optional reserve price for an auction (e.g., aprice below which the seller refuses to sell their item), a price forwhich the seller will immediately sell the item (e.g., a buyout-typelisting), or other pricing related information. The selling format 103may include information that specifies how the item is to be sold (e.g.,a fixed-price selling format, an auction-format, auction types includingEnglish, Dutch, Vickery, Chinese, Double, Reverse auctions, etc.), theduration of time the item may be available for sale or for auction, andother selling format information. The payment method 121 may includeinformation that specifies payment method(s) the seller will accept(e.g., payment service(s), credit card(s), checks, money orders, etc.).The shipping information 123 may include information that specifies thesellers shipping terms (e.g., who pays, locations the seller may or maynot ship the item, etc.). The item location 125 may include informationthat specifies the physical location from which the item may be shippedor picked up. The buyer requirements 127 may include information thatspecifies which buyers are blocked from bidding on or purchasing thelisted item based on criteria such as whether the buyer utilizes aspecific payment service, whether the buyer utilizes a specific creditcard, whether the buyer is registered in a specific country, the buyersreputation (e.g., the buyer has a feedback score of 1, 2, 3, or lower,the buyer has been identified as purchasing or winning an item in anauction and not paying for the item) and other related information.

The received information (e.g., item information 120) is supplementedwith supplemental information (e.g., item classification information131). Instances of item classification information 131 may include adomain 130, classification tags 97, and inference tags 99. Exampledomains 130 may include, “shoes”, “toys”, “books”, etc. Eachclassification tag 97 may include a tagged concept 136 and a taggedvalue 138. For example, an example tagged concept 136 for the domain 130“shoes” may include “brand” and corresponding example tagged values 138may include “Nike”, “Reebok” and “Adidas.” Adding classification tags 97(e.g., classification information) to the tagged item information 93structures the item information 120 and, in one embodiment, enables aconceptual search of the item information 120 (e.g., from the point ofview of the buyer, in the language of a buyer, etc.).

Each inference tag 99 may include an inference concept 141 and aninference value 143 (e.g., inferential information). The inference tag99 may be added to the item classification information 131 based on theitem information 120 or the classification tags 97. For example, theclassification engine 83 may infer from item information 120 that aglass item made by Corning has a “region of origin” in the United Statesbecause Corning makes glass in the United States, (e.g., inferenceconcept 141=“region of origin”, inference value 143=“North America”). Itshould also be appreciated that an inference tag 99 may be utilized tobroaden a tagged concept 136 or tagged value 138 and thereby bring users(e.g., a buyer or seller) together that may not otherwise be speakingthe same language even though they share a common interest ininformation (e.g., an item listing described by the item information120). For example, a seller may describe an item within the iteminformation 120 as being “ruby slippers”. However, the buyer may besearching for “red slippers.” In this instance the classification engine83 may add an inference tag 99 with the inference concept 141 “color”and the inference value 143 “red” based on a classification tag 97 witha tagged concept 136 “color” and a tagged value 138 “ruby.”

FIG. 7 is a block diagram illustrating search metadata 152, according toan embodiment. The search metadata 152 is shown to include an entry foreach domain 130 that may be defined in the computer-based system 12.Each domain 130 is associated with a set of classification rules 89, aset of inference rules 91 and a domain query 158. Each classificationrule 89 includes a classification clause 133 that may include anexpression (e.g., Boolean) and a classification predicate 135 that maybe executed if the classification clause 133 evaluates TRUE. Theclassification predicate 135 is shown to include a classificationconcept 140 and a classification value 142 (e.g., classificationinformation), as previously described. The classification rule 89 may beutilized by the classification engine 83 to apply a classification tag97 (e.g., classification concept 140 and a classification value 142).For example, the classification engine 83 may search the iteminformation 120 based on the classification clause 133 and, if theclassification clause 133 evaluates TRUE (e.g., if title contains“ruby”), the classification engine 83 may then execute theclassification predicate 135. In present example, the classificationpredicate 135 tags the corresponding item information 120 with theclassification concept 140 and a classification value 142 (e.g.,color=ruby). Henceforth the classification concept 140 and theclassification value 142 may respectively be referred to as the taggedconcept 136 and the tagged value 138 (e.g., color=ruby) with regard tothe tagged item information 93.

Each inference rule 91 includes an inference clause 137 that may includean expression (e.g., Boolean) and an inference predicate 139 that may beexecuted if the inference clause 137 evaluates TRUE. The inferencepredicate 139 is shown to include an inference concept 141 and aninference value 143 (e.g., inferential information), as previouslydescribed. The inference rule 91 may be utilized by the classificationengine 83 to apply an inference tag 99 (e.g., inference concept 141 andan inference value 143). For example, the classification engine 83 mayevaluate the item information 120 and classification tags 97 byutilizing inference clause 137. If the inference clause 137 evaluatesTRUE (e.g., if description 120 contains ‘red’ OR a tagged concept140—tagged value 138 contains ‘color=red’), the inference predicate 139may be executed, which in the present example tags the correspondingitem information 120 with additional information (e.g., the inferenceconcept 141 and the inference value 143) (e.g., color=ruby). Henceforththe added inference concept 141 and inference value 143 may collectivelybe referred to as an inference tag 99 with regard to the tagged iteminformation 93.

The domain query 158 may be utilized to identify item information 120 asincluded in the corresponding domain 130. The domain query 153 mayinclude an expression (e.g., Boolean) and a domain 130 that may beassociated with corresponding tagged item information 93, if theexpression (e.g., Boolean) evaluates TRUE. The domain query 153 may bedesigned by a computer program or an administrator. For example, theexpression (e.g., Boolean) associated with the domain “shoes” mayrequire a description 124 that contains ‘Nike’ and a title 122 thatcontains ‘shoes.’ Another embodiment may include an expression (e.g.,Boolean) that also requires an item specific 128 associated with a value134 that indicates “cross-training” or a listing category 126 thatindicates “athletic shoes.”

FIG. 8 is a flowchart illustrating a method 160, according to anembodiment, to facilitate searching of a data resource. Operationsperformed by the client machine 22 are illustrated on the left andoperations performed by the application server 28 are illustrated on theright.

Commencing at operation 162, the seller at the client machine 22 entersitem information 120 (e.g., an item listing) that is communicated to theapplication server 28, which then receives the item information 120(e.g., at operation 164). FIG. 30 illustrates a user interface screen165, according to an embodiment, that displays example item information120. The item information 120 includes a title 122, a listing category126, an item specific 128, and a description 124 that includes an ISBNnumber (e.g., 123456). For example, the title 122 may be the userselected title, “The Cat in the Hat Strikes Back.” The listing category126 shows that the user selected the listing category “Children'sBooks”. Other embodiments may show the user as having entered orselected multiple listing categories 126 (e.g., books, toys, children'sclassics, etc.). The item specific 128 further illustrates the conditionof the book as “new.” The value “new” may have been selected from a pulldown menu that includes multiple values including “old”, “used”, “good”,etc. The ISBN number (e.g., 123456) may be utilized as a trigger to addadditional information.

Returning to FIG. 8, at operation 166, the receiving module 422 searchesthe item information 120 (e.g., title 122, the description 124, thelisting category 126, item specific 128, etc.) to identify strings,values, or other information items that may trigger the addition ofcatalog information to the item information 120. For example, the ISBNnumber may trigger that addition of information (e.g., alphanumerictext, graphics, pictures, audio, multi-media, etc.) from an appropriatecatalog. Indeed, the ISBN number may uniquely identify the book “The Catin the Hat Strikes Back” and accordingly provide a trigger to includeinformation from a catalog that may further describe the book (e.g.,name of the author, number of pages, publisher, list price in newcondition, picture of author, audio recording of the first chapter,etc.). Other embodiments may include other types of catalogs that may beutilized to identify information (e.g., Universal Product Numbers,Universal Product Codes, Proper Nouns, etc.) that may provide a triggerto add additional information. In another embodiment the addition ofcatalog information may be performed before the item has been submittedat the time the seller is entering information for the item.

At operation 168, the receiving module 422 stores the item information120 in the database 36 and communicates the item information 120 to theclassification engine 83. At operation 170, the processing module 116generates a tagged item information 93 in the classification engine 83and stores the item information 120 in the tagged item information 93.Next, the processing module 116 reads a domain query 158 from the searchmetadata 158.

At decision operation 172, the processing module 116 determines if theitem described by the item information 120 entered by the user has beenfound with the domain query 158 by evaluating the expression (e.g.,Boolean) associated with the domain query 158 against the iteminformation 120. If the expression (e.g., Boolean) evaluates TRUE then abranch is made to operation 174. Otherwise a branch is made to decisionoperation 180.

At operation 174, the processing module 116 registers the iteminformation 120 as included in the current domain 130. For example, theprocessing module 116 may register the item information 120 by storingthe domain 130 in the item classification information 131 associatedwith the tagged item information 93.

At operation 176, the rule application module 118 applies classificationrules 89 to the item information 120 associated with the tagged iteminformation 93.

FIG. 9 illustrates a method 186, according to an embodiment, to evaluateinformation with classification rules. The method 186 commences atoperation 188 with the rule application module 118 reading or selectingthe next classification rule 89 from the search metadata 152 based onthe current domain 130.

At decision operation 190, the rule application module 118 utilizes theclassification clause 133 (e.g., ‘if title contains “ruby”’) associatedwith the classification rule 89 to evaluate the item information 120(e.g., title 122, description 124, listing category 126, item specific128, etc.). If the classification clause 133 evaluates to TRUE then abranch is made to operation 200. Otherwise a branch is made to decisionoperation 202.

At operation 200, the rule application module 118 executes theclassification predicate 135 (e.g., color=ruby) associated with theclassification rule 89 against the tagged item information 93. Forexample, rule application module 118 may attach or store theclassification predicate 135 as tagged item information 93. Theclassification predicate 135 may henceforth be referred to as aclassification tag 97 (e.g., color=ruby) with regard to the tagged iteminformation 93.

At decision operation 202, the rule application module 118 determines ifthere are more classification rules 89 in the current domain 130. Ifthere are more classification rules 89, then a branch is made tooperation 188. Otherwise the method 186 ends.

Returning to FIG. 8, at operation 178, the rule application module 118applies the inference rules 91 to the classification tags 97 associatedwith the tagged item information 93.

FIG. 10 illustrates a block diagram of a method 204, according to anembodiment, to evaluate information with inference rules 99. Commencingat operation 206, the rule application module 118 reads or selects thenext inference rule 91 from the search metadata 152 based on the currentdomain 130.

At operation 208, the rule application module 118 reads the next taggeditem information 93 (e.g., including classification tags 97) associatedwith the current domain 130. At decision operation 210, the ruleapplication module 118 utilizes the inference clause 137 (e.g., “ifdescription contains ‘ruby’ OR color=ruby”) associated with theinference rule 91 to evaluate the item information 120 (e.g., title 122,description 124, listing category 126, item specific 128) and theclassification tags 97 (e.g., color=red). If the inference clause 137evaluates to TRUE, then a branch is made to operation 212. Otherwise abranch is made to decision operation 214.

At operation 212, the rule application module 118 executes the inferencepredicate 139 (e.g., color=red) associated with the inference rule 91against the tagged item information 93. For example, the inferencepredicate 139 may be added or attached to the tagged item information93. Henceforth the inference predicate 139 may be referred to as aninference tag 99 with regard to the tagged item information 93.

At decision operation 214, the rule application module 118 determines ifmore tagged item information 93 is associated with the current domain130. If there is more tagged item information 93, then a branch is madeto operation 208. Otherwise a branch is made to decision operation 216.

At decision operation 216, the rule application module 118 determines ifmore inference rules 91 may be associated with the current domain 130.If the rule application module 118 determines there are more inferencerules 91, then a branch is made to operation 206. Otherwise processingends.

Returning to FIG. 8, at operation 180, the processing module 116determines if there are more domains 130. If the processing module 116determines there are more domains 130, then a branch is made tooperation 170. Otherwise the method 160 ends.

Another embodiment of the classification engine 83 may include a singleBoolean evaluation graph. The Boolean evaluation graph may be utilizedby the classification engine 83 to enhance the performance of Booleanevaluations. For example, a Boolean evaluation graph may evaluate alarge set of classification rules 89 and inference rules 91 against alarge set of information (e.g., item listings 85) while minimizing thetotal number of evaluation events computed by the classification engine83.

Generating a Query

FIG. 11 is a block diagram illustrating a system 107, according to anembodiment, to generate a query to search a data resource. The system107 is described to provide an example overview for what follows. Thesystem 107 includes search applications 57 and classification rules 89.The search applications 57 are shown to receive a keyword query 109 froma buyer 119 and respond by utilizing the classification rules 89 todetermine a domain 130, generate a concept query 111 and possiblydetermine keywords each of which are communicated back to the buyer 119.The concept query 111 includes one or more selected characteristics 113(e.g., classification information) that correspond to the keywords inthe keyword query 109 as determined by the classification rules 89. Insome instances keywords in the keyword query 109 may not correspond to aselected characteristic 113 and may be communicated back to the buyer assuch. Each selected characteristic 113 includes a selected concept 115and a selected value 117.

FIG. 12 is a block diagram illustrating search applications 57 andsearch metadata 152, according to an example embodiment. The searchapplications 57 include a computing module 221 and a query generationmodule 223. The computing module 221 receives the keyword query 109 fromthe buyer 119, and communicates a user interface back to the buyer 119that includes the concept query 111 and the domain 130. The querygeneration module 223 determines the domain 130 of the keyword query 109and applies classification rule 89 to the keyword query 109 to generatea concept query 111 and possibly identify keywords.

The search metadata 152 may include all of the defined domains 130 forthe computer-based system 12, as previously described. Each domain 130may be associated with a domain clause 129 and classification rules 89.The domain clause 129 includes a expression (e.g., Boolean) that may beutilized to evaluate the keyword query 109. If the domain clauseevaluates TRUE then the keyword query may be associated with the domain130. Each classification rule 89 includes a classification clause 133and a classification predicate 135, as previously described. Theclassification clause 133 includes an expression (e.g., Boolean) thatmay be utilized to evaluate keywords in the keyword query 109. If theclassification clause 133 evaluates TRUE then the classificationpredicate 135 (e.g., classification concept 140 and the classificationvalue 142) may be executed against the keyword query 109 therebyassociating the classification concept 140 and the classification value142 (e.g., classification information) with the keyword(s) in thekeyword query 109.

FIG. 13 illustrates a method 220, according to an embodiment, togenerate a query to search a data resource. Operations performed by aclient machine 22 are illustrated on the left and operations performedan application server 28 are illustrated on the right. The method 220commences at operation 222 where the user enters the keyword query 109.

FIG. 31 illustrates a user interface 224, according to an embodiment, toreceive a keyword query. The user interface 224 includes a dialogue box226 that may be utilized by the buyer 119 to enter a keyword query 109.The dialogue box 226 is shown to include the keyword query 109, “Nikeblack size 8.” The keyword query 109 includes keywords 228, “Nike”,“black” and “size 8.” It will be appreciated that keywords 228 mayinclude one or more words or alphanumeric expressions (e.g., size 8).The present example user interface does not require the user to manuallyidentify a domain 130; however, it will be appreciated that otherembodiments may include user interfaces that require the user tomanually identify a domain 130 that may be associated with the keywordquery 109 entered by the user. For example, in one embodiment a user maybe required to navigate a tree structure to locate a dialogue box 226 toenter a keyword query 109 that may be associated with a specific domain130.

Returning to FIG. 13, at operation 230, the computing module 221receives the keyword query 109 and communicates the keyword query 109 tothe query generation module 223 which determines whether the keywordquery 109 may be associated with one or more domains 130.

FIG. 14 illustrates a method 230, according to an embodiment, todetermine domains 130 based on the keyword query 109. The method 230commences at operation 233 with the query generation module 223 readingthe next domain clause 129 from the search metadata 152. The domainclause 129 may contain an expression (e.g., Boolean).

At decision operation 236, the query generation module 223 evaluates thekeyword query 109 with the domain clause 129 that may include anexpression (e.g., Boolean). If the expression (e.g., Boolean) evaluatesTRUE, then a branch is made to operation 238. Otherwise a branch is madeto decision operation 242.

At operation 238, the query generation module 223 associates the domain130 with the concept query 239 by registering the domain 130 to theconcept query 239.

At decision operation 242, the query generation module 223 determines ifthere are more domain clauses 129 to process. If there are more domainsdomain clauses 129 to process then a branch is made to operation 233.Otherwise the processing ends.

Returning to FIG. 13, at decision operation 249, the computing module221 determines if the keyword query 109 may be associated with more thanone domain 130. If the keyword query 109 may be associated with morethan one domain then a branch is made to operation 250. Otherwise abranch is made to operation 252.

At operation 250, the computing module 221 communicates a request to theuser to select one domain 130 from the domains 130 that were associatedwith the keyword query 109.

At operation 254, at the client machine 22, a user interface may bedisplayed to enable user-selection of a domain 130. FIG. 32 illustratesthe user interface 256, according to an example embodiment, to select adomain 130. The user interface 256 includes the keyword query 109 anddomains 130 (e.g., “shoes”, “running suits” and “golf equipment”) thatmay be selected by the user.

Returning to FIG. 13, at the client machine 22, at operation 260, theuser selects the “shoes” domain 130, the selection being communicated tothe application server 28.

At operation 252, at the application server 28, the query generatingmodule 231 receives the “shoes” domain 130 and utilizes the “shoes”domain 130 and the keyword query 109 “Nike Black Size 8” to determinethe selected characteristics 113.

FIG. 15 illustrates a method 252, according to an embodiment, todetermine selected characteristics 113 based on the keyword query 109and the domain 130. The method 252 commences at operation 262 with thequery generation module 223 utilizing the domain 130 that is associatedwith the keyword query 109 to read a classification rule 89 from thesearch metadata 152.

At decision operation 264, the query generation module 223 utilizes theclassification clause 133 associated with classification rule 89 toevaluate the longest set of keywords (e.g., words) in the keyword query109. If the classification clause 133 evaluates TRUE, then a branch ismade to operation 266. Otherwise a branch is made to operation 265.

At operation 265, the query generation module 223 removes the firstkeyword from the keyword query 109.

At operation 266, the query generation module 223 registers theclassification predicate 135 (e.g., color=ruby) associated with theclassification rule 89 to the concept query 239. Henceforth theclassification predicate 135 may be referred to as a selectedcharacteristic 113.

At operation 267, the query generation module 223 removes the keyword(s)228 that evaluated TRUE from the keyword query 109.

At decision operation 269, the query generation module 223 determines ifthere are more keywords in the keyword query 109. If there are morewords, a branch is made to decision operation 264. Otherwise a branch ismade to decision operation 268.

At decision operation 268, the query generation module 223 determines ifthere may be more classification rules 89. If there are moreclassification rules 89 then a branch is made to operation 262 toevaluate the entire keyword query 109. Otherwise the method 252 ends.

Returning to FIG. 13, at operation 270, at the application server 28,the computing module 221 communicates a user interface including thekeyword query 109, the domain 130, and the concept query 239 to thebuyer 119 at the client machine 22.

At operation 272, at the client machine 22, the user interface isdisplayed to the user. FIG. 33 illustrates a user interface 278,according to an example embodiment, to display the keyword query 109,the domain 130, and the concept query 239. The user interface 278 isshown to include the keyword query 109 “Nike Black Size 8” and theconcept query 111 including three selected characteristics 113,“Color—Black”, “Brand—Nike”, and “Shoe Size—8.” The selectedcharacteristics 113 are respectively shown to include selected concepts115 (e.g., “Color”, “Brand”, “Shoe Size” and selected values 117 (e.g.,“Black”, “Nike”, and “8”). Another example may include keyword(s) 228(e.g., keywords 228 included in the keyword query 109 that may not haveevaluated TRUE with regard to classification clauses 133).

Another embodiment of a system that receives a keyword query andgenerates a concept query, a domain, and keywords may include a singleBoolean evaluation graph. The Boolean evaluation graph may be utilizedby the system to enhance the performance of Boolean evaluations. Forexample, the system may utilize the Boolean evaluation graph to evaluatea large set of classification rules 89 against a keyword query 109 whileminimizing the total number of evaluation events computed by the system107.

Identify Data Items & Canceling Characteristics

FIG. 16 is a block diagram illustrating a system 293, according to anembodiment, that receives a keyword query and generates a user interfacethat includes the keyword query, a concept query, browsingcharacteristics and information (e.g., item listings 85). The system 293is described to provide an overview for what follows.

The system 293 includes search applications 57, classification rules 89,and display instructions 302. The search applications 57 are shown toreceive a keyword query 109 “Nike Black Size 8” that includes keywords228 that may be entered by a buyer 119 with a user interface 295. Thesearch applications 57 receive the keyword query 109 and utilize theclassification rules 89 and the display instructions 302 to generate theuser interface 297.

The user interface 297 includes the keyword query 109, the domain 130“shoes”, the concept query 111 “Color—Black, Brand—Nike, Shoe Size—8”,multiple browsing sets 303 (e.g., “Product Type”, “Shoe Style”, “PriceRange”) and information (e.g., item listings 85) found based on theconcept query 111. The keyword query 109, the domain 130 and the conceptqueries 111 have been previously described. The concept query 111 isshown to include multiple selected characteristics 113 (e.g.,“Color—Black”, “Brand—Nike, and “Shoe Size 8”). Each selectedcharacteristic 113 includes a selected concept 115 (e.g., “Color”) and aselected value 117 (e.g., “Black”). For example, the buyer 119 may addselected characteristics 113 to the concept query 111 and/or cancelselected characteristics 113 from the concept query 111. The buyer 119may add a selected characteristic 113 to the concept query 111 byselecting a browsing characteristic as described below. The buyer maycancel selected characteristics 113 by selecting one or more “cancel”buttons (not shown) each of which may be associated with a particularselected characteristic 113. The browsing sets 303 are selected by thesearch applications 57 based on the cumulative selected characteristics113 (e.g., generated from the keyword query 109, the selected browsingcharacteristics, and the cancellations) according to a specified order.In other words, the most interesting browsing sets 303 may be presentedbefore the least interesting browsing sets 303, the level of interestdetermined from the point of view of the buyer 119 by an administrator.Other embodiments may determine the level of buyer interest for aparticular browsing set 303 by monitoring user selections of browsingsets 303. Some embodiments may determine the level of buyer interest fora particular browsing set 303 by monitoring the previous selections ofbrowsing sets 303 made by the buyer. Each browsing set 303 is shown toinclude a browsing concept 284 (e.g., “Product Type”) and multiplebrowsing values 286 (e.g., “Men's Shoes”, “Women's Shoes”, etc.). Thebuyer 119 may select one or more browser values 286 (e.g., “Men'sShoes”), thereby effectively selecting one or more browsingcharacteristic 287 (e.g., “Product Type—Men's Shoes”). Henceforth theselected browsing characteristic 287 may be referred to as a selectedcharacteristic 113 that may be included in the cumulative selectedcharacteristics 113 that may be utilized to select the browsing sets303, compute counts and find information (e.g., item listings 85).

FIG. 17 is a block diagram illustrating search applications 57 andsearch metadata 152, according to an embodiment. The search applications57 include a determining module 298 and a generating module 300. Thedetermining module 298 determines selected characteristics 113,determines the size of areas on a user interface to display information(e.g., item listings 85, browsing sets 303, etc.), determinesinformation (e.g., item listings 85) to display, and determines browsingsets 301 to display. The determining module 298 determines the selectedcharacteristics 113 based on the concept query 111 (e.g., generated froma keyword query 109), browsing characteristic(s) 287 that may have beenselected, and/or selected characteristics 113 that may have beencancelled). In addition, the determining module 298 determines or findsinformation (e.g., item listings 85) and determines or finds browsingsets 303 based on the determined selected characteristics 113. Finally,the generating module 300 may generate counts values that may beassociated with browsing values 286.

The search metadata 152 is shown to be organized by domain 130, aspreviously described. Each domain 130 includes a set of displayinstructions 302 that include multiple browsing sets 303. Each browsingset 303 includes a browsing concept 284 and multiple browsing values286. The browsing set 303 may be presented to a buyer 119 who may selecta single browsing value 286 thereby effectively selecting a browsingcharacteristic 287 (e.g., a browsing concept 284 and browsing value286). The browsing sets 303 may be ordered according to the interest ofmost users. For example, a user may be most interested in the browsingsets 303 that appear at the top of the display instructions 302 andleast interested in the browsing sets 303 that appear at the bottom ofthe display instructions. Accordingly, the display instructions 302 maybe utilized by the determining module 298 to determine which browsingsets 303 to present to the user based on the selected characteristics113 and the limited area on the display which precludes the ability topresent all browsing sets 303 on a single display.

FIG. 18 illustrates a classification engine 114, according to anembodiment. The classification engine 114 includes tagged iteminformation 93 entries that include item information 120 and itemclassification information 131 including classification tags 97 andinference tags 99, as previously described. The determining module 298utilizes the selected characteristic(s) 113 associated with the conceptquery 111 and, in some instances, keywords 228 (e.g., keywords 228contained in the keyword query 109 that may not have evaluated TRUE withany classification clause 133) to determine or find information (e.g.,item listings 85)(e.g., “Items Found”).

FIG. 19 illustrates a method 304, according to an embodiment, toidentify data items for browsing. Operations for the client machine 22appear on the left and operations for the application server 28 appearon the right. At operation 306, the user enters a keyword query 109 thatis communicated to the application server 28.

At operation 308, at the application server 28, the search applications57 receive the keyword query 109 and generate a concept query 111 thatincludes one or more selected characteristics 113. For example, thesearch applications 57 may receive the keyword query “Black Nike Size 8”and generate a concept query 111 for the domain 130 “shoes” thatincludes three selected characteristics 113 (e.g., “Color—Black”,“Brand—Nike”, and “Shoe Size—8”). Next, the search applications 57generate a user interface based on the selected characteristics 113associated with the concept query 111.

FIG. 20 illustrates a method 310 to generate a user interface based onselected characteristics 113 and keyword(s) 228, according to anembodiment. The method 310 commences at operation 312 where thedetermining module 298 determines a set of information (e.g., itemlistings 85).

FIG. 21 illustrates a method 312, according to an example embodiment, todetermine a set of item listings 85 based on the selectedcharacteristics 113 and keyword(s) 228. The method 312 commences atoperation 314 where the determining module 298 reads the item (e.g.,tagged item information 93) from the classification engine 114 that maybe associated with the domain 130 “shoes.”

At decision operation 318, the determining module 298 utilizes thekeyword(s) 228 and the selected characteristics 113 associated with theconcept query 111 to form an expression and to determine if theexpression evaluates TRUE. For example, the determining module 289 mayutilize “‘Color=Black’ AND ‘Brand=Nike’ AND ‘Shoe Size=8’” to evaluatethe classification tags 97 and/or inference tags 93. In addition, thedetermining module may utilize the keywords 228 (e.g., keywords 228contained in the keyword query 109 that may not have evaluated TRUE withany classification clause 133) to evaluate the item information 120. Ifthe expression (e.g., Boolean) evaluates TRUE then a branch is made tooperation 324. Otherwise a branch is made to decision operation 322.

At operation 324, the determining module 298 registers the item as found(e.g., “Item Found”).

At decision operation 322, the determining module 298 determines ifthere are more items associated with the domain 130 “shoes” in theclassification engine 114. If there are more items then a branch is madeto operation 314. Otherwise the method ends.

Returning to FIG. 20, at operation 326, the determining module 298determines the browsing sets 303 to display to the user based on theselected characteristics 113. For example, the determining module 298may access the appropriate display instructions 302 to determine themost interesting browsing sets 303 sufficient to occupy the availableroom on the user interface.

FIG. 22 illustrates a method 326, according to an embodiment, todetermine browsing sets 303. The method 326 commences at operation 313with the determining module 298 reading the next browsing set 301 fromthe search metadata 152 based on the appropriate domain 130. Forexample, the determining module 298 may read the browsing set 301 thatmay be associated with the display instructions 302 that may beassociated with the domain 130 “shoes.”

At operation 315, the determining module 298 reads the next selectedcharacteristic 113. At decision operation 317, the determining module298 compares the selected concept 115 associated with the selectedcharacteristic 113 with the browsing concept 284 associated with thebrowsing set 301. If the selected concept 115 and the browsing concept284 match, then the determining module 298 branches to operation 321(e.g., do not display a browsing set that corresponds to a selectedconcept). Otherwise the determining module 298 branches to decisionoperation 319.

At decision operation 319, the determining module 298 determines ifthere are more selected characteristics 113. If there are more selectedcharacteristics 113 then a branch is made to operation 315. Otherwise abranch is made to operation 321.

At operation 321, the determining module 298 registers the browsing set301 to be displayed on the user interface.

At decision operation 323, the determining module 298 determines ifanother browsing set 303 may be displayed on the user interface. Ifanother browsing set 303 may be displayed then a branch is made todecision operation 325. Otherwise processing ends.

At decision operation 325, the determining module 298 determines ifthere are more browsing sets 303. If there are more browsing sets 303then a branch is made to operation 313. Otherwise processing ends.

The above described embodiment selects browsing sets 301 forpresentation to the user based on the order of browsing sets 301 as theyappear in the display instructions 302. Accordingly, the displayinstructions 302 determine a fixed order of interest for the display ofbrowsing sets 301 to the user. In other embodiments the fixed order ofinterest may be temporarily overridden by the cancellation of a selectedcharacteristic 113 with regard to the selected characteristic 113. Inthis instance the cancelled selected characteristic 113 may temporarilybe considered to be of maximum interest to the user and thereforedisplayed as a browsing set 301 to the user subsequent to cancellationof the corresponding selected characteristic 113. Accordingly, the fixedorder of interest may be temporarily overridden to accommodate a userthat may want to cancel a browsing value 286 that may be associated withthe cancelled selected characteristic 113.

Returning to FIG. 20, at operation 328 the generating module 300generates a count for each of the browsing values 286 associated withthe browsing sets 303 that may be displayed on the user interface.

FIG. 23 illustrates the method 328, according to an embodiment, togenerate counts for browsing values 286. At operation 330, thegenerating module 300 reads the next item that may have been found basedon the selected characteristics 113 and keyword(s) 228 (e.g., based onoperation 324).

At operation 332, the generating module 300 reads the next browsing set303 from the appropriate display instructions 302. For example, theappropriate display instructions 302 may be associated with a domain 130that matches the domain 130 associated with the concept query 111.

At operation 333, the generating module 300 reads the next browsingvalue 286 associated with the current browsing set 303.

At decision operation 334, the generating module 300 evaluates thecurrent item with an expression (e.g., Boolean) including the currentbrowsing concept 284 and the current browsing value 286 (e.g.,color=black). If the expression (e.g., Boolean) evaluates TRUE, then abranch is made to operation 336. Otherwise a branch is made to decisionoperation 337.

At operation 336, the generating module 300 increments the appropriatecounter (e.g., the counter corresponding to the current browsing concept284 (e.g., color) and the current browsing value 286 (e.g., black).

At decision operation 337, the generating module 300 determines if thereare more browsing values 286 associated with the current browsing set301. If there are more browsing values 286, then a branch is made tooperation 333. Otherwise a branch is made to decision operation 338.

At decision operation 338, the generating module 300 determines if thereare more browsing sets 303. If there are more browsing sets 303 then abranch is made to operation 332. Otherwise a branch is made to decisionoperation 340.

At decision operation 340, the generating module 300 determines if thereare more found items (e.g., found based on the selected characteristics113, operation 324). If there are more found items then a branch is madeto operation 330. Otherwise processing ends.

Returning to FIG. 19, at operation 360, at the application server 28,the search applications 57 communicate the generated user interface tothe client machine 22.

At operation 362, the client machine 22 displays the generated userinterface to the user. FIG. 34 illustrates a generated user interface363, according to an embodiment. The user interface 363 includes akeyword query 109 (e.g., “Black Nike Size 8”), a domain 130 (“Shoes”), aconcept query 111 (e.g., Color=Black, Brand=Nike, Shoe Size=8), browsingconcepts 284 (e.g., “Product Type”, “Shoe Style”, “Price Range”),browsing values 286 (e.g., “Men's Shoes”, “Women's Shoe's, etc.), counts365 associated with each of the browsing values 286, and information(e.g., item listings 85) that may have been found based on the selectedcharacteristics 113.

At the client machine 22, the user selects “Men's Shoes”, therebyindicating the selection of a browsing characteristic 287 (e.g.,“Product Type—Men's Shoes”). Returning to FIG. 19, at operation 364, theclient machine 22 communicates the browsing characteristic 287 selectionto the application server 28.

At operation 372, at the application server 28, the determining module298 receives the selected characteristics 113 associated with theconcept query 111 and the browsing characteristic 287 and determines thecumulative selected characteristics 113. For example, the determiningmodule 298 may determine the cumulative selected characteristics 113 toinclude “Color—Black”, “Brand—Nike”, “Shoe Size—8”, “Product Type—Men'sShoes.” Next, the determining module 298 and the generating module 300may utilize the cumulative selected characteristics 113 and keyword(s)228 to generate a user interface, as previously described in method 310on FIG. 20.

At operation 374, the generated user interface is communicated to theclient machine 22.

At operation 376, the client machine 22 receives and displays thegenerated user interface. FIG. 35 illustrates a generated user interface378, according to an embodiment. The user interface 378 illustrates theadditional selected characteristic 113, “Product Type—Men's Shoes.” Inaddition, the browsing set 303 associated with the browsing concept 284“Shoe Width” has been added to the user interface 378 thereby providingthe user with the three most interesting browsing sets 303 (e.g., “ShoeWidth”, “Shoe Style”, “Price Range”) based on the cumulative selectedcharacteristics 113. Each browsing set 303 is shown to be associatedwith a “select more” button 305 that may be selected to presentadditional browsing values 286 that may be associated with the browsingset 303. In addition, the user interface 378 is shown to includemultiple browsing set buttons 307 (e.g., “Condition”, “Shoe Sub-Style”,“Buying Options”) that may be selected by the user to select thecorresponding named browsing sets 303. It will be appreciated that thebrowsing set buttons 307 reading from left to right provide the userwith the next three most interesting browsing sets 303.

It should be noted that the counts 365 have been recomputed and theinformation (e.g., item listings 85)(e.g., “Items Found”) updated basedon the cumulative selected characteristics 113 and keyword(s) 228. Theuser interface 378 further includes “Cancel” buttons 381 associated witheach of the selected characteristics 113 thereby enabling the user tocancel a particular selected characteristic 113 without removing theremaining selected characteristics 113. In the present example, the userselects the “Cancel” button 381 associated with the selectedcharacteristic 113 “Shoe Size—8”; however, it should be noted that theuser may have selected a “Cancel” button 381 associated with any of theselected characteristics 113 (e.g., “Color—Black”, “Brand—Nike”, “ShoeSize 8” or “Product Type—Men's Shoes”) and the remaining selectedcharacteristics 113 may have been utilized to find information (e.g.,item listings), determine the most interesting browsing sets 301 fordisplay, and generate counts for the associated browsing values 286.Returning to FIG. 19, at operation 390, the client machine 22communicates the concept query 111, the selected browsing characteristic287 (e.g., “Product Type—Men's Shoes”) and the cancelled selectedcharacteristic (e.g., “Shoe Size—8”) to the application server 28.

At operation 392, at the application server 28, the determining module298 receives the concept query 111, the selected browsing characteristic287 (e.g., “Product Type—Men's Shoes”) and the cancelled selectedcharacteristic (e.g., “Shoe Size—8”) and determines the cumulativeselected characteristics 113. For example, the determining module 298may determine the cumulative selected characteristics 113 to include“Color—Black”, “Brand—Nike”, “Product Type—Men's Shoes.” Next, thedetermining module 298 and the generating module 300 may utilize thecumulative selected characteristics 113 to generate a user interface, aspreviously described in method 310 on FIG. 20.

At operation 394, the generated user interface is communicated to theclient machine 22.

At operation 396, the client machine 22 receives and displays thegenerated user interface. FIG. 36 illustrates a generated user interface398, according to an embodiment. The user interface 398 is shown to nolonger include the cancelled selected characteristic 113 “Shoe Size—8.”In addition, the browsing set 303 that was associated with the browsingconcept 284 “Shoe Width” has been displaced by the browsing set 303associated with the browsing concept “Shoe Size” (e.g., therebyproviding the user with the most interesting browsing sets 303 inaccordance with the cumulative selected characteristics 113). Finally,the counts 365 have been recomputed and the information (e.g., itemlistings 85)(e.g., “Items Found”) have been updated based on the updatedselected characteristics 113 (“Color—Black”, “Brand—Nike”, “ProductType—Men's Shoes”). In another embodiment the browsing options (e.g.,browsing sets 301 and browsing set buttons 307) may be minimized todisplay additional information (e.g., item listings 85).

Dynamic Display

FIG. 37 illustrates a user interface 400, according to an embodiment, tominimize the display of browsing options. The user interface 400minimizes the display of browsing options and maximizes the display ofinformation (e.g., item listings 85) based on an item count droppingbelow a threshold level. For example, the user interface 400 may includea count of “20” items found 472, the count determined by the determiningmodule 298 to be below a configurable threshold resulting in theminimization of browsing options on the user interface 400. To this end,the browsing sets 301 may not be displayed on the user interface 400though the browsing set buttons 307 (e.g., “Condition”, “ShoeSub-Style”, “Buying Options”) may continue to be displayed on the userinterface 400. In place of the browsing sets 301 additional information(e.g., item listings 85) may be displayed. Accordingly, a count of itemlistings 85 that falls below a threshold may trigger the generation of auser interface that emphasizes found information (e.g., item listings85) rather than browsing options.

Another embodiment of a system that receives a keyword query andgenerates a user interface that includes the keyword query, a conceptquery, browsing characteristics and information (e.g., item listings 85)may include a single Boolean evaluation graph. The Boolean evaluationgraph may be utilized by the system to enhance the performance ofBoolean evaluations. For example, the system may utilize the Booleanevaluation graph to evaluate a large set of selected characteristics 113and keywords 228 against information (e.g., item listings 85) whileminimizing the total number of evaluation events computed by the system.In yet another embodiment, the system may utilize a Boolean evaluationgraph to evaluate a large set of browsing characteristics 287 againstinformation (e.g., item listings 85).

Processing Back Button Selection

FIG. 24 is a block diagram illustrating user interfaces 401 and browsercontrols 403, according to an embodiment. The user interfaces 401 may bedisplayed at a client machine and include a user interface 407, a userinterface 409, and a user interface 411. The user interface 409 mayinclude a client application program (e.g., applet, JavaScript, etc.)that may execute at the client machine to generate and display the userinterfaces 409 and 411. The browser controls 403 include a back button405 that may be selected by a user thereby triggering a browser todisplay the previous user interface to the user.

The user interfaces 401 illustrate a problem due to interference betweenthe client application program and the browser. For example, a user atthe client machine may select a button 415 (e.g., “A”) from the userinterface 407 thereby triggering the browser at the client machine torequest the user interface 409 from a server. In response, the servercommunicates the user interface 409, including a client applicationprogram (e.g., JavaScript), to the client machine where the clientapplication program executes to display the user interface 409 to theuser. Next, the user, at the client machine, may select a button 415(e.g., “B”) from the user interface 409 that may be processed by theclient application program at the client machine to generate and displaythe user interface 411. If the user now selects the back button 405 thenthe browser may respond by accessing the server to retrieve and displaythe user interface 407 instead of the user interface 409, as expected bythe user. The browser responds in this manner because the browseroperates without knowing that the JavaScript has executed to update thedisplay with the user interface 411.

FIG. 25 is a block diagram illustrating a system 420, according to anembodiment, to process a browser back button. The system 420 includesthe network based computer-based system 12 that includes an applicationserver 28 or server machine that communicates over a network 14 with aclient machine 22, as previously described. The client machine 22 isshown to include a programmatic client 18 (e.g., browser), a hiddenframe 432, hidden user interfaces 425, 427 429, a visible frame 430, anda visible user interface 426 that includes a client application program428 (e.g., script, program, applet, etc.) and user interface elements418. The programmatic client 18 (e.g., browser) may be utilized torequest the visible user interface 426 and hidden user interfaces 425,427 429 from the application server 28. In addition, the clientapplication server 28 may be executed by the programmatic client 18 togenerate additional user interfaces (not shown) for display in thevisible frame 430 at the client machine 22. To this end, the visible andhidden frames 430, 432 may be respectively associated with datastructures that are utilized by the programmatic client 18 and theclient application program 428.

A frame is a browser construct that may be utilized to partition aparticular area of the display. In the present example, the hidden frame432 is not partitioned an area of the display. Accordingly, theprogrammatic client 18 may request the hidden user interfaces 425, 427,429 from the application server 28; however, displaying the hidden userinterfaces 425 427, 429 does not result in generating user interfaceelements that are visible to the user. In the present application, thehidden user interfaces 425, 427, 429, are utilized merely to enableproper processing of the back button 405. Further, the hidden userinterfaces 425, 427, 429, are identified as static thereby triggeringthe programmatic client 18 to store the hidden user interfaces 425, 427,429, in a cache (not shown) at the client machine 22.

The computer-based system 12 is shown to include an application server28 that includes search applications 57 that include a receiving module422 and a communication module 424. The receiving module 422 receivesrequests for the visible user interface 426 and the hidden userinterfaces 425, 427, 429 and generates the requested user interfaces426, 425, 427, 429 or reads the requested user interfaces 426, 425, 427,429 from a database 36. The communication module 424 communicates thevisible and hidden user interfaces 426, 425, 427, 429 to the clientmachine 22.

FIG. 26 is a block diagram further illustrating software componentsassociated with the client machine 22, according to an embodiment. Theclient machine 22 is shown to include the programmatic client 18 (e.g.,browser), a cache 434, user interface history 436, a visible frame 430and a hidden frame 432.

The cache 434 may be utilized by the programmatic client 18 to store andretrieve static user interfaces (e.g., hidden user interfaces 425, 427,429) for the purpose of minimizing the delay between a request for astatic user interface and an update of the display. Accordingly, thecache 434 may be utilized to retrieve the static user interface insteadof the application server 28.

The user interface history 436 includes frame 438 and URL 431 pairs thatmay be stored by the programmatic client 18 to record user interfacesthat have been displayed in the respective visible and hidden frames430, 432. For example, in one embodiment, the user interface history 436may operate like a stack whereby the programmatic client 18 may push aframe 438 and URL 431 pair onto the stack responsive to the userrequesting a user interface (e.g., corresponding to the URL 431) to bedisplayed in the frame 438 (e.g., visible frame 430, hidden frame 432,etc.). Conversely, the programmatic client 18 may pop one or more frame438 and URL 431 pairs off the stack responsive to the user selecting theback button, the programmatic client 18 redisplaying the previous userinterface in the designated frame. Accordingly, the user interfacehistory 436 may operate as a first-in last-out buffer thereby providinga mechanism that preserves the order of user interfaces selected by theuser and enabling the user to review the user interfaces in backwardsorder responsive to user repeatedly selecting the back button 405.

The visible frame 430 and hidden frame 432 include programmatic clientvisible and hidden frame statuses 435, 437, visible and hidden frameobjects 443, 445, client application program visible and hidden framestatuses 439, 441, the visible user interfaces 426, 466, 492 and thehidden user interfaces 425, 427, 429.

The programmatic client visible and hidden frame statuses 435, 437respectively include URLs 447, 449. The programmatic client 18 mayutilize the visible and hidden frame statuses 435, 437 to determine ifthe client application program 428 may have requested the programmaticclient 18 to request a user interface from the application server 28 tobe displayed in the respective frame 430, 432.

The visible and hidden frame objects 443, 445 each include URLs 451, 453that may be monitored and updated by the programmatic client 18 and theclient application program 428. The URLs 451, 453 indicate the requestedor actual user interface displayed in the respective visible frames 430and hidden frames 432.

The client application program visible and hidden frame statuses 439,441 respectively include URLs 455, 467. The client application program428 may utilize the visible and hidden frame statuses 439, 441 todetermine if the programmatic client 18 may have updated the userinterface associated with the respective visible frame 430 or hiddenframe 432.

The visible user interfaces include the visible user interface 426,mode=Default, the visible user interface 466, mode=More, and the visibleuser interface 492, mode=All. The hidden user interfaces include thehidden user interface 425, mode=Default, the hidden user interface 427,mode=More, and the hidden user interface 429, mode=All.

The visible user interface 426 includes the client application program428 and user interface elements 448 previously described. The userinterface elements 448 may include graphics, text, or alphanumericstrings that may be displayed on the client machine 22 and when selectedby the user may result in the communication of an event to the clientapplication program 428. For example, client application program 428 mayreceive an event that triggers the generation and display of the visibleuser interface 466 or 492 responsive to the user selecting a “MORE” or“ALL” user interface element 448, respectively.

The programmatic client 18 monitors the back button 405 and the URLs451, 453 associated with the respective visible and hidden frame objects443, 445. The programmatic client 18 may respond to a selection of theback button 405 or a change in the URL 451, 453. The programmatic client18 may respond to the selection of the back button 405 by utilizing theuser interface history 436 to retrieve the requested user interface fromthe cache 434 or the application server 28. The programmatic client 18may respond to a change in the URL 451 by retrieving the visible userinterface identified by the URL 451 including the visible user interface492, mode=Default. The programmatic client 18 may respond to a change inthe URL 453 by retrieving the hidden user interface identified by theURL 453 including the hidden user interface 425, mode Default or thehidden user interface 427, mode=More or the hidden user interface 429,mode=All.

The client application program 428 responds to the user selecting theuser interface elements 448 and monitors the URLs 441, 453 associatedwith the respective visible and hidden frame objects 443, 445. Theclient application program 428 may respond to the selection of a userinterface element 448 by generating and displaying the visible userinterface 426, mode=Default, or the visible user interface 466,mode=More, or the visible user interface 492, mode=All, in the visibleframe 430 and by updating the corresponding URL 453 in the hidden frameobject 445 thereby triggering the programmatic client to retrieve thecorresponding requested hidden user interface 425, 427, or 429.

FIG. 27 is an interactive flow chart illustrating a method 450,according to an embodiment, to process a back button at a client machine22. Illustrated on the right are operations performed by theprogrammatic client 18 and illustrated on the left are operationsperformed by the client application program 428. The method 450commences, at operation 452, at the client machine 22 with theprogrammatic client 18 (e.g., browser) responding to a user entering akeyword query by communicating a request to the application server 28for the corresponding visible use interface 426. For example, therequest, without keywords, may include the following URL:

http://search/VisibleUserInterface?Mode=DEFAULT

FIG. 28 is an interactive flow chart illustrating a method 452,according to an embodiment, to request a user interface. Illustrated onthe right are operations performed at the application server 28 andillustrated on the left are operations performed at the client machine22. The method 452 commences, at operation 457, at the client machine 22where the programmatic client 18 pushes an entry onto the top of theuser interface history 436 by storing the requested URL 431 and theassociated frame 438. In the present example, the programmatic client 18stores the above described URL and the visible frame 430.

At decision operation 459, the programmatic client 18 determines if therequested user interface (e.g., corresponding to the URL) may be presentin the cache 434. If the user interface is present in the cache 434,then a branch is made to operation 460. Otherwise a branch is made tooperation 461.

At operation 461, the programmatic client 18 may communicate the requestfor the user interface to the application server 28.

At operation 463, at the application server 28, the receiving module 422receives the request and generates the requested user interface or readsthe requested user interface from a database 36.

At operation 467, the communication module 424 communicates therequested user interface to the client machine 22 where it may be storedin the cache 434 at operation 469.

At operation 471, the programmatic client 18 displays the user interfaceelements in the appropriate frame (e.g., hidden or visible) and themethod 452 ends. In the present example, the programmatic client 18displays the user interface elements 448 associated with the visibleuser interface 426 at the client machine 22. FIG. 38 illustrates thevisible user interface 426 and browser controls 403, according to anembodiment. The browser controls 403 include a back button 405 that maybe selected by the user to return to the previous user interface. Thevisible user interface 426 includes a concept query 111, browsing sets303 and item found 472 including information (e.g., item listings 85),as previously described. In addition, each browsing set 303 includesbrowsing values 286 each of which may be associated with a count aspreviously described, and a more button 470 (e.g., “MORE”). The browsingvalues 286 may be selected to further narrow the search of items found472. For example, selecting the price range $30.00-$40.00 may result infinding items that match the concept query (e.g., Color—Black,Brand—Nike, Size—8) in the selected price range (Price—$30.00-$40.00).The more button 470 may be selected by a user to display additionalbrowsing values 286 with regard to a particular browsing set 303 (e.g.,TOE TYPE, SHOE STYLE, PRICE RANGE).

Returning to FIG. 27, at the client machine 22, at operation 454, theprogrammatic client 18 invokes the client application program 428 (e.g.,script).

At operation 474, the client application program 428 communicates arequest to the programmatic client 18 to request the hidden userinterface 425. For example, the request may include the following URL:

http://search/HiddenUserInterface/static?Mode=DEFAULT

Next, the client application program 428 stores the above described URLin the URL 455 of the client application program visible frame status439.

At operation 476, the programmatic client 18 requests the hidden userinterface 425 by communicating the above described URL to theapplication server 28. For example, the method 452 may be utilized aspreviously described. Accordingly, after retrieval of the hidden userinterface 425 the visible and hidden frame statuses 435, 437, thevisible and hidden frame objects 443, 445, and the visible and hiddenframe statuses 439, 441 each include a URL designating the “DEFAULT”mode.

At the operations 460, the client applications program 428 and theprogrammatic client 18 monitor the URLs 451, 453 associated with therespective visible and hidden frame objects 443, 445; however, themonitoring may be preempted by user selections at the client machine 22.

FIG. 29A illustrate a method 490, according to an embodiment, to processa user selection of the “more” user interface element 448. The method490 commences at the client machine 22, at operation 465, with the userselecting the “MORE” button 470 associated with the “Price Range”browsing set 303 on the user interface 426. In response, the clientapplication program 428 generates and displays the visible userinterface 466 (e.g., Mode=MORE). It should be noted that the clientapplication program 428 generates and displays the visible userinterface 466 without accessing the application server 28 or the cache434.

FIG. 39 illustrates a visible user interface 466 and browser controls403, according to an embodiment. The browser controls 403 include a backbutton 405. The visible user interface 466 includes a concept query 111,a single browsing set 303 associated with “Price Range” includingadditional (e.g., “MORE”) browsing values 286 and items found 472 thatincludes information (e.g., item listings 85). Each browsing value 286may be associated with a check box 468 and a count. The user may selectone or more check boxes 468 thereby further narrowing the search forinformation (e.g., item listings 85). For example, the user may selectthe check box 468 associated with the price range $5.00-$10.00 and thecheck box 468 associated with the price range $35.00-$40.00.Accordingly, the search for information (e.g., item listings 85) mayinclude the following search criteria “color=black” and “brand=Nike” and“size=8” and ((price range=$5.00-$10.00) or (pricerange=$35.00-$40.00)).

Returning to FIG. 29A, at operation 474, the client application program428 updates the URL 446 associated with the hidden frame object 445 andthe URL 467 associated with the client application program hidden framestatus 441 and the process ends. For example, the client applicationprogram 428 may store the following URL:

http://search/HiddenUserInterface/static?Mode=MORE

Returning to FIG. 27, at the client machine 22, at decision operation477, the programmatic client 18 determines if there has been a hiddenframe 432 forward change. For example, the programmatic client 18 maycompare the URL 449 associated with the programmatic client hidden framestatus 437 with the URL 453 associated with the hidden frame object 445to determine if the client application program 428 may be requesting aforward change of the hidden frame 432. If the URL 449 is different fromthe URL 453, then the client application program 428 may be requesting aforward change of the user interface associated with the hidden frame432 and a branch is made to operation 478. Otherwise a branch is made todecision operation 480.

At operation 478, the programmatic client 18 requests the user interfaceidentified with the URL 453 associated with the hidden frame object 445.For example, the programmatic client may utilize the method 452, aspreviously described on FIG. 28. Accordingly, the user does not perceiveany change to the display at the client machine 22 because the hiddenframe 432 does not include displayable user interface elements.

FIG. 29B illustrate a method 491, according to an embodiment, to processa user selection of the “ALL” user interface element 448. The method 491commences at the client machine 22, at operation 480, with the userselecting the “ALL” button 473 on the visible user interface 466. Inresponse, the client application program 428 generates and displays thevisible user interface 492 without accessing the application server 28or the cache 434.

FIG. 40 illustrates a visible user interface 492 and browser controls403, according to an embodiment. The browser controls 403 include a backbutton 405. The visible user interface 492 includes the concept query111, the browsing set 303 associated with “Price Range”, and the itemsfound 472. The browsing set 303 includes “ALL” browsing values 286associated with “Price Range.” Each browsing value 286 may be associatedwith a check box 468 and a count. The user may select one or more checkboxes 468 thereby further narrowing the search for the items found 472.

Returning to FIG. 29B, at operation 484, the client application program428 updates the URL 453 associated with the hidden frame object 445 andthe URL 467 associated with the client application program hidden framestatus 441 and the process ends. For example, the client applicationprogram 428 may store the following URL:

http://search/HiddenUserInterface/static?Mode=ALL

Returning to FIG. 27, at the client machine 22, at operation 477, theprogrammatic client 18 determines if there has been a forward change ofthe URL 453 associated with the hidden frame object 445, as previouslydescribed. If the programmatic client 18 determines there has been aforward change of the URL 453, then a branch is made to operation 478.Otherwise a branch is made to decision operation 481.

At operation 478, the programmatic client 18, requests the hidden userinterface 229 based on the URL stored in the URL 453 associated withhidden frame object 445. For example, the programmatic client 18 mayutilize the method 452, as previously described on FIG. 28.

FIG. 29C illustrate a method 462, according to an embodiment, to processa user selection of the back button 405. The method 462 commences at theclient machine 22, at operation 486, with the user selecting the backbutton 470 from the browser control 403. In response, the programmaticclient 18 may pop the top two entries off the user interface history436, the second entry including the frame 438 and the URL 431 of theprevious user interface displayed by the programmatic client 18. Forexample, the programmatic client 18 may determine that the previous userinterface displayed in the hidden frame 432 may be identified with thefollowing URL:

http://search/HiddenUserInterface/static?Mode=MORE

At operation 488, the programmatic client 18 requests the user interface427 identified by the URL described above. For example, the method 452may be utilized to request the user interface 427, as previouslydescribed.

Returning to FIG. 27, at the client machine 22, at decision operation481, the client application program 428 determines if there has been abackward change of the URL 453 associated with the hidden frame object445. For example, the client application program 428 may compare the URL467 (e.g., associated with the client application program hidden framestatus 441) with the URL 453 (e.g., associated with the hidden frameobject 445) to determine if the client application program 428 processeda back button 405 request associated with the hidden frame 432. If theURL 467 is different from the URL 453 then a branch is made to operation483. Otherwise a branch is made to decision operation 477.

At operation 483, the programmatic client 18, updates the visible frame430 based on the user interface elements 448 identified by the URL 453.For example, the following URL 453 may signal the programmatic client 18to update the visible frame 430 with the visible user interface 466 thatcorresponds to the “MORE” mode:

http://search/HiddenUserInterface/static?Mode=MORE

For example, the visible frame may be updated with the visible userinterface 466 as illustrated on FIG. 39, as previously described.

FIG. 41 shows a diagrammatic representation of machine in the exampleform of a computer system 500 within which a set of instructions, forcausing the machine to perform any one or more of the methodologiesdiscussed herein, may be executed. In alternative embodiments, themachine operates as a standalone device or may be connected (e.g.,networked) to other machines. In a networked deployment, the machine mayoperate in the capacity of a server or a client machine in server-clientnetwork environment, or as a peer machine in a peer-to-peer (ordistributed) network environment. The machine may be a server computer,a client computer, a personal computer (PC), a tablet PC, a set-top box(STB), a Personal Digital Assistant (PDA), a cellular telephone, a webappliance, a network router, switch or bridge, or any machine capable ofexecuting a set of instructions (sequential or otherwise) that specifyactions to be taken by that machine. Further, while only a singlemachine is illustrated, the term “machine” shall also be taken toinclude any collection of machines that individually or jointly executea set (or multiple sets) of instructions to perform any one or more ofthe methodologies discussed herein.

The example computer system 500 includes a processor 502 (e.g., acentral processing unit (CPU) a graphics processing unit (GPU) or both),a main memory 504 and a static memory 506, which communicate with eachother via a bus 508. The computer system 500 may further include a videodisplay unit 510 (e.g., a liquid crystal display (LCD) or a cathode raytube (CRT)). The computer system 500 also includes an alphanumeric inputdevice 512 (e.g., a keyboard), a cursor control device 514 (e.g., amouse), a disk drive unit 516, a signal generation device 518 (e.g., aspeaker) and a network interface device 520.

The disk drive unit 516 includes a machine-readable medium 522 on whichis stored one or more sets of instructions (e.g., software 524)embodying any one or more of the methodologies or functions describedherein. The software 524 may also reside, completely or at leastpartially, within the main memory 504 and/or within the processor 502during execution thereof by the computer system 500, the main memory 504and the processor 502 also constituting machine-readable media.

The software 524 may further be transmitted or received over a network526 via the network interface device 520.

While the machine-readable medium 522 is shown in an example embodimentto be a single medium, the term “machine-readable medium” should betaken to include a single medium or multiple media (e.g., a centralizedor distributed database, and/or associated caches and servers) thatstore the one or more sets of instructions. The term “machine-readablemedium” shall also be taken to include any medium that is capable ofstoring, encoding or carrying a set of instructions for execution by themachine and that cause the machine to perform any one or more of themethodologies of the present invention. The term “machine-readablemedium” shall accordingly be taken to include, but not be limited to,solid-state memories, optical and magnetic media, and carrier wavesignals.

Thus, methods and systems to browse data items have been described.Although the present invention has been described with reference tospecific example embodiments, it will be evident that variousmodifications and changes may be made to these embodiments withoutdeparting from the broader spirit and scope of the invention.Accordingly, the specification and drawings are to be regarded in anillustrative rather than a restrictive sense.

We claim:
 1. A method including: receiving item information, over anetwork at a computer based system, from a first client machine andstoring, at a computer based system, the item information in a firstlisting, the first client machine being associated with a seller, thereceiving item information being executed by at least one processer;receiving a plurality of selections, over the network at a computerbased system, from at least one client machine, the at least one clientmachine being associated with a user, the plurality of selections beingmonitored, at a computer based system, to identify an elevated level ofinterest of a first user for a first plurality of browsing sets, thefirst plurality of browsing sets including a first browsing set, thereceiving the plurality of selections being executed by at least oneprocesser; receiving a query from, over the network at a computer basedsystem, from the at least one client machine, the query including atleast one keyword, the receiving the query being executed by at leastone processer; automatically selecting, at a computer system, a secondplurality of browsing sets from a third plurality of browsing sets basedon at least one keyword in the query and further automatically selectingthe first browsing set from the second plurality of browsing sets basedon the elevated level of interest of the first user for the firstbrowsing set, the first browsing set including a browsing concept, theautomatically selecting being executed by at least one processer;generating, at a computer system, a first user interface including thebrowsing concept, the user interface further including at least tworanges of browsing values that are associated with the browsing concept,the at least two ranges of browsing values including a first range ofnumeric browsing values and a second range of numeric browsing values,the first range of numeric browsing values being associated with a firstselection mechanism and the second range of numeric browsing valuesbeing associated with a second selection mechanism, the generating beingexecuted by at least one processer; receiving, over a network via thefirst user interface at a computer based system, at least twoselections, the receiving the at least two selections includingreceiving a first selection via the first selection mechanismidentifying the first range of numeric browsing values and receiving asecond selection via the second selection mechanism identifying thesecond range of numeric browsing values, the receiving the at least twoselections to cause a search of a data resource to be narrowed to aplurality of listings that respectively include item informationincluding a value that matches at least one value that is selected fromthe first range of numeric browsing values and the second range ofnumeric browsing values, the receiving the at least two selections beingexecuted by at least one processer; and identifying, at a computersystem, at least two listings that are stored in the data resource, theidentifying including identifying the first listing based on the firstrange of numeric browsing values and an evaluation of item informationthat is included in the first listing, the identifying further includingidentifying a second listing based on the second range of numericbrowsing values and an evaluation of item information that is includedin the second listing, the identifying being executed by at least oneprocesser.
 2. The method of claim 1, wherein the item information thatis stored in the first listing is associated with the at least tworanges of browsing values based on at least two rules selected from agroup of rules consisting of rules that are utilized to classify theitem information and rules that infer additional information.
 3. Themethod of claim 2, wherein the item information includes at least one ofa price, a selling duration, and an auction duration.
 4. The method ofclaim 3, further including adding catalog information to the iteminformation that is included in the first listing responsive toidentifying item information including at least one of an USBN number, aUniversal Product Number, a Universal Product Code and a proper noun. 5.The method of claim 1, wherein the first listing is associated with aplurality of browsing concepts respectively associated with a pluralityof ranges of browsing values.
 6. The method of claim 1, wherein the atleast two selections are combined with the query to identify the atleast two listings.
 7. The method of claim 1, wherein the user interfaceenables the buyer to request a second user interface includingadditional ranges of browsing values associated with the browsingconcept.
 8. A system including: a processor and executable instructionsaccessible on a computer-readable medium that, when executed, cause theprocessor to perform operations comprising: receive item information,over a network at a computer based system, from a first client machineand store, at a computer based system, the item information in a firstlisting, the first client machine is associated with a seller; receive aplurality of selections, over the network at a computer based system,from at least one client machine, the at least one client machine isassociated with a user, the plurality of selections being monitored, ata computer based system, to identify an elevated level of interest of afirst user for a first plurality of browsing sets, the first pluralityof browsing sets including a first browsing set; receive a query from,over the network at a computer based system, from the at least oneclient machine, the query including at least one keyword; automaticallyselect, at a computer based system, a second plurality of browsing setsfrom a third plurality of browsing sets based on at least one keyword inthe query and further automatically select the first browsing set fromthe second plurality of browsing sets based on the elevated level ofinterest of the first user for the first browsing set, the firstbrowsing set including a browsing concept; generate, at a computer basedsystem, a first user interface including the browsing concept, the userinterface further including at least two ranges of browsing values thatare associated with the browsing concept, the at least two ranges ofbrowsing values including a first range of numeric browsing values and asecond range of numeric browsing values, the first range of numericbrowsing values being associated with a first selection mechanism andthe second range of numeric browsing values being associated with asecond selection mechanism; receive, over a network via the first userinterface at a computer based system, at least two selections, thereceipt of the at least two selections including receipt of a firstselection via the first selection mechanism to identify the first rangeof numeric browsing values and receipt of a second selection via thesecond selection mechanism to identify the second range of numericbrowsing values, the receipt of the at least two selections to cause asearch of a data resource to be narrowed to a plurality of listings thatrespectively include item information including a value that matches atleast one value that is selected from the first range of numericbrowsing values and the second range of numeric browsing values; andidentify, at a computer based system, at least two listings that arestored in the data resource, the identification including identificationof the first listing based on the first range of numeric browsing valuesand an evaluation of item information that is included in the firstlisting, the identification further including identification of a secondlisting based on the second range of numeric browsing values and anevaluation of item information that is included in the second listing.9. The system of claim 8, wherein the item information that is stored inthe first listing is characterized with the first range of numericbrowsing values based on a rule from a group of rules consisting ofrules that are utilized to classify the item information and rules toinfer additional information.
 10. The system of claim 8, wherein theitem information is that is stored in the first listing includes atleast one of a price, a selling duration, a selling format, and anauction duration.
 11. The system of claim 10, wherein the selling formatis selected from a group of formats consisting of a fixed-price formatand an auction format.
 12. The system of claim 10, further including areceiving module to wherein the operations further comprising: searchthe item information that is included in the first listing and identifyat least one of a USBN number, a Universal Product Number, a UniversalProduct Code and a proper noun to add catalog information to the iteminformation.
 13. The system of claim 9, wherein the at least twolistings are associated with a plurality of browsing conceptsrespectively associated with a plurality of ranges of browsing values.14. The system of claim 13, wherein the at least two browsing selectionsare combined with the query to identify the at least one listing. 15.The system of claim 9, wherein the user interface enables the buyer torequest a second user interface including additional browsing valuesassociated with the browsing concept.
 16. The system of claim 8, whereinthe operations further comprising: receives, via the user interface, atleast two selections.
 17. The system of claim 16, wherein the at leasttwo selections include a first selection that identifies the first rangeof numeric browsing values and a second selection that identifies thesecond range of numeric browsing values.
 18. The system of claim 8,wherein the operations further comprising: receives the item informationthat is included in the first listing from a seller and the query from abuyer.
 19. The method of claim 1, wherein the first range of numericbrowsing values consists of a lower numeric limit and an upper numericlimit.
 20. The method of claim 1, further comprising receiving an orderof interest for the second plurality of browsing sets from anadministrator.
 21. A machine readable medium having no transitorysignals and storing a set of instructions that, when executed by amachine, cause the machine to: receive item information, over a networkat a computer based system, from a first client machine and store, at acomputer based system, the item information in a first listing, thefirst client machine is associated with a seller; receive a plurality ofselections, over the network at a computer based system, from at leastone client machine, the at least one client machine is associated with afirst user, the plurality of selections is monitored, at a computerbased system, to identify an elevated level of interest of the firstuser for a first plurality of browsing sets, the first plurality ofbrowsing sets including a first browsing set; receive a query from, overthe network at a computer based system, from the at least one clientmachine, the query including at least one keyword; automatically select,at a computer based system, a second plurality of browsing sets from athird plurality of browsing sets based on at least one keyword in thequery and further automatically select the first browsing set from thesecond plurality of browsing sets based on the elevated level ofinterest of the first user for the first browsing set, the firstbrowsing set including a browsing concept; generate, at a computer basedsystem, a first user interface including the browsing concept, the userinterface further including at least two ranges of values that areassociated with the browsing concept, the at least two ranges ofbrowsing values including a first range of numeric browsing values and asecond range of numeric browsing values, the first range of numericbrowsing values is associated with a first selection mechanism and thesecond range of numeric browsing values is associated with a secondselection mechanism; receive, over a network via the first userinterface at a computer based system, at least two selections, includinga first selection that is received via the first selection mechanismthat identifies the first range of numeric browsing values and a secondselection that is received via the second selection mechanism thatidentifies the second range of numeric browsing values, the receipt ofthe first and second selections to cause a search of a data resource tobe narrowed to a plurality of listings including item informationincluding a value that matches at least one value that is selected fromthe first range of numeric browsing values and the second range ofnumeric browsing values; and identify, at a computer based system, atleast two listings that are stored in the data resource, theidentification of the first listing is based on the first range ofnumeric browsing values and an evaluation of item information that isincluded in the at least one listing, the identification of a secondlisting is based on the second range of numeric browsing values and anevaluation of item information that is included in the second listing.